M.S. Theses

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Browsing M.S. Theses by Subject "Adaptive control systems."

Now showing 1 - 4 of 4
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    An adaptive control structure combining model reference adaptive controllers and stochastic self-tuning regulators
    (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 1985., 1985.) Kerestecioğlu, Feza, 1961- .; Istefanopulos, Yorgo.
    Discrete-time model reference adaptive controllers for single-input single-output minimum -phase plants in deterministic environment are studied. Both explicit and implicit reference models are considered. Similarities and dualities between the model reference adaptive controllers and stochastic self-tuning regulators are indicated and the behaviour of model reference adaptive controllers in stochastic environment is analyzed. Finally, an adaptive control structure combining model reference adaptive controllers and stochastic self-tuning regulators is discussed, which is suitable for regulation and tracking objectives in both deterministic and stochastic environment. Simulations on a digital computer are done to justify theoretical results and investigate various features of the adaptive control structures mentioned.
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    Automatic topic categorization of Turkish Faxed Bank documents in the presence of OCR errors
    (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2014., 2014.) Öztürk, Seçil.; Saraçlar, Murat.; Sankur, Bülent.
    The technological advances in the last decades facilitated the easy transfer and storage of huge amounts of scanned soft documents. This improvement brings the challenge of automatically classifying big, unbalanced, multi-class, noisy and relatively short text data, which is the scope of this thesis. This study addresses the real world problem, classifying bank order documents of Yap Kredi Bank. A corpus of academic paper abstracts, which resembles the original problem in terms of class complexity and document length is also collected and used. Combinations of methods for balancing, pre-processing data, feature extraction, feature selection and classi cation are discussed in this study. The unbalanced data are balanced by sampling documents randomly or according to their noise and information content. For Optical Character Recognizer errors, rst the word is assessed as corrigible or incorrigible in terms of its potential to be corrected. For corrigible words, four methods are used for correction, which are domain speci c glossary based model, language model based Hidden Markov Model and normal or agressive sequential correction models. In order to minimize redundant data, Named Entity tagging, Morfessor and F5 stemming are used. Latent Dirichlet Allocation and Term Frequency Inverse Document Frequency features are used. To classify balanced classes, the best technique is Term Frequency Inverse Document Frequency features with Support Vector Machines, which is tested and proven for both the Yap Kredi Bank Orders and Academic Paper Abstracts datasets with up to 92% performance for 12 classes for the Yap Kredi Bank Orders Dataset.
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    Center of gravity estimation and rollover prevention using Kalman filtering techniques
    (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2010., 2010.) Dere, Ali Dinçer.; Akar, Mehmet.
    Due to its impacts on human safety and its economical cost, vehicle rollover is a very important safety issue that attracts the attention of major vehicle manufacturers and researchers. The objective of this thesis is to design a control system that only becomes active in emergency situations and prevents rollover by applying differential braking to the vehicle. More specifically, the main focus of this thesis is to estimate several unknown vehicle parameters, including the center of gravity height, that has major role in roll over, by using Kalman Filter algorithm. Subsequently, the estimated center of gravity height is used in determining the amount of differential braking force. Extensive simulations are carried out in MATLAB to demonstrate the superior performance of the proposed method.
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    Microprocessor application for adaptive posicast control of lightly damped systems
    (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 1985., 1985.) Karuv, Süleyman Bahadır.; Istefanopulos, Yorgo.
    The problem of compensating a feedback system which is very lightly damped has long confronted control engineers. Numerous schemes have been utilized with varying degrees of succes. This work investigates and applies one such scheme, Half-cycle Posicast, which was introduced by Otto J. M. Smith. This scheme has several advantages. It reduces overshoot and resonant peaking thus allowing higher forward gain to be used. This in turn reduces steady-state errors. The problem of compensating a second order, lightly damped linear feedback system by means of Half-cycle Posicast with microprocessor application is examined and the results of analog computer simulations are shown. The sensitivity of behavior to variations.in system parameters is examined and some degree of adaptivity to changes of parameters is reached.